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Title of Journal: Ann Inst Stat Math

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Abbravation: Annals of the Institute of Statistical Mathematics

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Springer-Verlag

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10.1007/s00128-012-0942-y

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1572-9052

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Local Emphasis Type="Italic"c/Emphasis and E

Authors: Holger Dette Viatcheslav B Melas Andrey Pepelyshev
Publish Date: 2006/05/11
Volume: 58, Issue: 2, Pages: 407-426
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Abstract

In this paper we investigate local E and coptimal designs for exponential regression models of the form sum i=1k a iexpleftmu ixright We establish a numerical method for the construction of efficient and local optimal designs which is based on two results First we consider for fixed k the limit μ i → γ i = 1 k and show that the optimal designs converge weakly to the optimal designs in a heteroscedastic polynomial regression model It is then demonstrated that in this model the optimal designs can be easily determined by standard numerical software Secondly it is proved that the support points and weights of the local optimal designs in the exponential regression model are analytic functions of the nonlinear parameters μ 1 μ k This result is used for the numerical calculation of the local Eoptimal designs by means of a Taylor expansion for any vector μ 1 μ k It is also demonstrated that in the models under consideration Eoptimal designs are usually more efficient for estimating individual parameters than Doptimal designs

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  2. Smoothing algorithms for state–space models
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  4. Conditional independence, conditional mixing and conditional association
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  8. Full likelihood inferences in the Cox model: an empirical likelihood approach
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  11. Higher-order accurate polyspectral estimation with flat-top lag-windows
  12. A class of rank-based test for left-truncated and right-censored data
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  16. On sum of 0–1 random variables I. Univariate case
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  18. Testing Homogeneity in Weibull Error in Variables Models
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  20. Proportional odds frailty model and stochastic comparisons
  21. Multiplicity distributions in a two-component branching process
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